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The concept of Business Intelligence is something that is alien to very few people these days. With newer tools emerging everyday to help solve the crisis of data management, most organisations have already moved in or have plans to use Business Intelligence in solving their crisis. Power BI is Microsoft’s latest BI tool mainly aimed to help everyone analyse and visualize their data. This Power BI tutorial will give you a complete insight into Power BI in the following sequence:
You may go through this Microsoft Power BI recording where our Power BI Training expert has explained the topics in a detailed manner with examples that will help you to understand the concepts better.
This video will help you to understand what is BI as well as Power BI. Then moving on in this video we have discussed the components and building blocks of Power BI.
In an age where Business Intelligence has become a bigger domain than most trending technologies, if you ask twenty people what the term business intelligence means, you are likely to get ten different answers. So let me put it in the simplest terms without losing the technicality of it. Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis. To put it simply, Business intelligence is the technology which gets the right data to the right people, at the right time so that they can make more effective business decisions.
The image below shows benefits of Business Intelligence.
Over the years, the process of business intelligence has grown and adapted to help solve almost all the challenges while dealing with data by involving newer tools and techniques. The change that Business Intelligence has seen over the years can be divided into 3 waves, so let us continue with our Power BI tutorial and take a look these three waves.
1st Wave: Technical (IT To End User)
During the first wave of business intelligence, the end user had to be dependent on the IT department for data insights. This is because it was not possible for end users to create visualizations/ reports on their own as tools available required technical knowledge. This dependence on IT department for insights resulted in more efforts and time consumption to get the updates done.
2nd Wave: Self-Service (Analyst To End User)
The second wave gave analysts access to BI. Now, people with some knowledge of analytics could use the BI tools. This meant more teams had access to BI and more people could have better data insights, this eased the role of IT teams.
3rd Wave: Everyone (End User)
The third wave has made it easier to access data and create reports, visuals to get better business insights. The introduction of tools like Power BI made this transition easy. Now anybody who has basic understanding of the data can create reports to build intuitive and shareable dashboards.
In a nutshell, data visualization is nothing but the pictorial or graphical representation of information/ data. It provides insights into complex data sets by communicating the key aspects in more intuitive and meaningful ways. Data visualization lies at the intersection of design, communication and information science.
Even though data visualization has been termed as the key skill for research in the twenty-first century, it goes way back. It existed in the late 18th century and can be traced back when invented geometrical charts. His bar charts were used to represent Scotland’s imports and exports of 17 countries in 1781. These bar charts constituted a pure solution to the problem of discrete quantitative comparison.
The way, human brain processes information, it is easier to use images, charts or graphs to understand and to visualize large amounts of complex data, than to go through spreadsheets or reports. Take any image for example, we all know the phrase ‘An image is worth a thousand words’. This is completely true because images aren’t just a mere collection of pixels, they also hold a lot of information. This information in visual form is easy to understand than reading the same facts in text form.
Data visualization is a quick and easy way to convey concepts or information in a universal manner. Data visualization can help to:
Following points make Power BI one of the prominent tools for data visualization. This Power BI tutorial would be incomplete without understanding these points.
Power BI, well this name has been in the BI market for quite a long time. Microsoft team has worked for a long time to build a big umbrella called Power BI, this umbrella is a combination of a strong visualization, data analysis and a cloud based tool.
To define it, Power BI is a business analytics service provided by Microsoft. It provides interactive visualizations with self-service business intelligence capabilities, where end users can create reports and dashboards by themselves, without having to depend on information technology staff or database administrators.
Power BI also gives you cloud-based BI services, known as “Power BI Services”, along with a desktop based interface, called “Power BI Desktop”. It offers data warehouse capabilities, including data preparation, data discovery and interactive dashboards. In March 2016, Microsoft released an additional service called Power BI Embedded on its Azure cloud platform which enables the user to analyse data easily, perform various ETL operations and deliver reports with Power BI.
Power BI gateways let you connect with SQL Server databases, Analytical Services, and many other data sources to your dashboard in Power BI and reporting portals, embed Power BI reports and dashboards to give you a unified experience. The image below shows Power BI’s general workflow.
Power BI has following components:
The following image shows Power BI’s architecture.
Power BI’s architecture has three phases. The first two phases partially use ETL (Extract, Transform and Load) to handle the data. Let us take a look at these phases one by one:
An organisation can be required to deal with data that comes from different sources. The data from data sources can be in different file formats. The data is first extracted from different sources which can be your different servers or databases etc. This data is then integrated in a standard format and then stored at a common area called as staging area.
The integrated data is still not ready for visualization because the data needs processing before it can be presented. This data is pre-processed or cleaned. For example, missing values or redundant values are removed from the data set. After the data is cleaned, business rules are applied to the data and it is transformed into presentable data. This data is then loaded into the Data Warehouse.
So once the data is loaded and processed now it can be visualized much better with use of various visualizations that Power BI has to offer. Use of reports, dashboards help one represent data in more intuitive manner. These visuals, reports help business end users to take business decisions based on the insights.
Everything you do in Power BI can be broken down into following building blocks. A good understanding of these building blocks would help you understand concepts and will let you create detailed and complex reports.
The basic building blocks of Power BI are the following:
A visual representation of data is called visualization. For example, a chart or a graph can be used to represent data visually. Power BI gives you different visualization types, which keep getting updated with time. Following image shows some commonly used visualizations:
Visualizations can be simple or they can be visually complex. However, visualization aims at presenting data in such a way that it gives you more insights in the context, which is otherwise difficult to discern from simple data files.
We know that data-set is nothing but a collection of data or information. Power BI harnesses this data to create visualizations. It can be a simple data set or a combination of many different sources, which can be filtered and combined to provide a different data set altogether.
For example, you can pull together data from many different sources like different database fields, an excel table, and online results of some email campaign to create the data set. Having said that, you may want to filter your data before you bring it into Power BI. Filtering lets you focus on the data that matters to you. The image below shows a sample data set.
With the data set ready, you are free to create visualizations and display different portions of that data set in different ways, and with this, you gain insights.
A collection of visualizations that appear together on one or more pages is a report in Power BI. It is a collection of items that are related to one another.
You can create visualizations, on multiple different pages if necessary, and arrange them in a way that suits your story best. The image below shows a sample report.
A Power BI dashboard is a single page interface. It is often called a canvas, that uses visualizations to tell a story. Because it is limited to one page, a well-designed dashboard contains only the most-important elements of that story. The visualizations you see on the dashboard are called tiles and are pinned to the dashboard from reports.
In Power BI, a tile is a single visualization found in a report or on a dashboard. It’s the rectangular box that contains each individual visual.
Power BI gives you the freedom to move or arrange tiles, so you can present the data the way you want to, even while you’re creating a report or a dashboard. You can make the tiles bigger, change their height or width, and snuggle them up to other tiles the way you want.
So this was about Power BI’s building blocks, now I am going to take this Power BI tutorial a step further with a demonstration of creating a simple report using Power BI. However, there are few prerequisites to get started. First of all you need a ‘Power BI Desktop’ installed on your system, this is an interface where you can create reports. It can be downloaded for free. You may use this link to download Power BI Desktop.
You will be required to login with an organisational email ID like an institute Email ID or your Email ID of the organisation which you work for. It is important you create an account, because this will give you access to Power BI Service which is a must to publish your reports and create dashboards.
Once you have downloaded the Power BI Desktop. You would be needing a data set to visualize it. I would be using the finance data set created by Microsoft and it can be downloaded using this link.
The image below shows how a Power BI Desktop’s interface looks. The highlighted section in blue colour, on the left panel shows the report, data and relationship workspaces. By default, the report workspace will open. This is where you create reports. Below the reports workspace is the data workspace which is used to see the imported data sets. Last tab is the relations tab which gives you relationship between different variables in a data set, if they are well defined. On the right side, you will see visualizations and field workspace.
So let us import the finance data set in Power BI. You can click on the Get Data tab which is highlighted in the image below and load the data for usage.
I have gone ahead and added the finance data set. Power BI will ask you whether you want to load data or edit it. I have simply loaded it because the data set won’t be needing any editing.
You can view by clicking on the data tab on the left hand corner of the interface. If you have taken a look at the data you would understand it is simple data about few countries and their sales in general. In the right corner of the screen, you can see all the fields the data set has. Use the image below for reference.
Let us go back to our report workspace and create a simple report. The first step is to select a visualization. I would be using a clustered column chart visualization. When you click on the desired visualization, a template is created in the report workspace.
Now that we have selected a visualization, I am going to visualize sales and profits on Y-axis and date on X-axis. Since you are using Power BI, you don’t have to worry about complexities of choosing the axis. You just select the fields and it is reflected in the graph. Refer the image below.
You can even drag and drop fields on the visualization and the changes would be reflected immediately. In the image below, I have dragged the ‘profit’ field.
You can resize these visualizations by just dragging the borders or even move the image by just clicking and placing it anywhere in the workspace.
You can even change graphics based on timelines by just clicking. I have changed the yearly representation of the sales data in the above graph to monthly representation. And the insights have changed completely. You can refer the image below to see those changes.
Below the visualization panel you have fields and format tabs. You perform statistical operations like calculating mean, median, sum and even filter data for various parameters by using fields tab. You can use different colour schemes to to make your visualization more appealing and insightful by using the format tab. The image below shows how you can change the colour of the fields used in the visualization.
We have successfully created a visualization. Creating visualisations in Power BI is as simple as this. I hope by now, you are comfortable enough to create visualizations on your own. You can even go ahead and publish your reports to the web. The image below shows how to publish a report in Power BI.
Once you publish a report, Power BI will give you a link. You can click on that link and view your report after it is published. For your reference, I have created few other visualizations in a report and published it. You can that report in the form of GIF below. The following have been visualized:
When you create a report like this in your Power BI Desktop, you will get insights and you can drill-down into the stats. This can be achieved by clicking on different fields that are present in your visualizations.
You may choose the visuals that suits your requirement and experiment accordingly. There are a lot of visualizations to try and experiment. Also, when it comes to visualization, no two individuals visualize data in the same way, so your reports may turn out differently. So this is how you can create reports and edit them using Power BI.
Let us now move ahead and take a look at the last topic of this Power BI tutorial.
Let us take a look at this use case and understand how Wirepas used Power BI to visualize a massive amount of sensor-collected data quickly, easily, and effectively.
About the company
Wirepas focuses on providing the most reliable, optimised, and scalable device connectivity to its customers. With Wirepas, customers can digitalise their current business processes and innovate for new disruptive models. Wirepas has its headquarters in Tampere, Finland, and offices in France, Germany, South Korea and the United States and was established in 2010 in Tampere.
Wirepas technology collects a wide variety of data through its connectivity service. Every wireless device built on Wirepas software technology can collect and send a huge amount of data. This data is collected in several ways and then stored in database. Visualizing this data is key to getting an overview of the current state of “things” tracked by the technology. Wirepas had following obstacles to overcome:
Wirepas used Power BI to overcome all the above mentioned challenges. Let us take a look at the solution.
Solution and delivery
Acquire the data
The data was imported from different sources and cleaned up using Power BI and Query Editor.
Design the report using Power BI Desktop
After importing and cleaning up the data from 1 million sensors, Power BI was used to design dashboard that enabled the customers, to get overviews of all data and enable them to drill down to one single parcel and the parcel history.
Create a Power BI workspace
To create the Power BI workspace in Azure, the Power BI-CLI was used. Back then, there was no UI available to create workspaces for Power BI in Azure. Therefore, they used the Power BI command line tool for managing Power BI Embedded workspace collections.
Embed Power BI in a web app
Power BI Embedded enabled developers to embed reports in almost every kind of app. This was the easiest way to embed the report into a website.
The following architecture was used to overcome the overall problem:
This was a smart way for Wirepas to bring their IP to the cloud in an easy and fast implementation. The whole project needed limited calling time, consulting, and implementation.
For Bosch Connected World, this was an easy demonstration of complex data based on Azure and Power BI Embedded. Since the workshop, Wirepas has won several new customers who are using its products and dashboards powered by Power BI Embedded.
If you need a detailed understanding of this use case then you can refer this link , which will direct you to the page where the actual case study was published.
This brings us to the end of this blog. I hope you liked this Power BI tutorial blog. This was the first blog of the Power BI series. This Power BI tutorial will be followed by my next blog, which will focus on Power BI Dashboards, do read that as well.
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